Automated modeling and morphologic analysis of deep medullary veins at 7T MRI in patients with cognitive impairment

Deep medullary veins (DMVs) support cerebral venous drainage. They may display abnormal changes in patients with cognitive impairment. They can be visualized by multi-echo gradient echo imaging at 7T. This study proposed a segmentation and tracking method based on deep learning and shortest-path optimization. It automatically quantified the morphologic parameters of DMVs from the vascular model. These characteristics of DMVs correlated with the patients’ cognitive scores, and might reflect the pathology of vascular lesions in cognitive impairment.